Healthcare Interoperability & Clinical Data Specialist

Contech Systems Inc. is seeking a Healthcare Interoperability & Clinical Data Specialist to support clinical data integration and interoperability initiatives. The role focuses on onboarding, analyzing, transforming, validating, and supporting healthcare data from external and internal sources using CCD/C-CDA, HL7, FHIR, REST APIs, Python, and SQL, while coordinating with vendors and stakeholders to resolve integration issues and assess data quality.

Responsibilities:

• Analyze and interpret inbound clinical data from new and existing sources, with particular emphasis on CCD/C-CDA documents, FHIR resources, HL7 messages, and API-based data exchange
• Evaluate the structure, semantics, completeness, consistency, and clinical usability of data received from EHRs, health information exchanges, data aggregators, and other interoperability partners
• Develop, enhance, and maintain processes to parse, extract, normalize, transform, and validate clinical data from XML, JSON, delimited files, APIs, and other healthcare data formats
• Map source data elements and clinical concepts to normalized internal data models and, where applicable, FHIR resources and standard terminologies such as LOINC, SNOMED CT, ICD-10-CM, CPT/HCPCS, and RxNorm
• Lead or support onboarding of new clinical data sources by performing source discovery, sample-file analysis, field and code mapping, data profiling, validation, defect identification, and production-readiness assessment
• Create automated data quality checks and reconciliation processes to identify missing sections, malformed documents, inconsistent coding, duplicate clinical facts, unexpected values, and source-specific anomalies
• Investigate interoperability and data integration issues, perform root cause analysis, and coordinate resolution with EHR vendors, health information exchanges, data aggregators, IT teams, and business stakeholders
• Develop and maintain reusable Python and SQL utilities for clinical data profiling, parsing, comparison, validation, exception handling, and large-scale analysis
• Work with FHIR resources and RESTful APIs to retrieve, inspect, validate, and transform clinical data, including understanding resource relationships, references, profiles, bundles, and terminology bindings
• Analyze CCD/C-CDA documents at both document and section level, including templates, entries, identifiers, codes, dates, providers, encounters, observations, procedures, and other clinically relevant content
• Assess whether clinical data from new sources is suitable for downstream use cases such as quality measurement, supplemental data, clinical analytics, population health, and HEDIS reporting
• Create and maintain technical documentation including source inventories, interface specifications, data dictionaries, mapping documents, validation rules, data lineage, known limitations, and onboarding procedures
• Participate in user acceptance testing, production support, source certification, release validation, and ongoing monitoring of interoperability and clinical data pipelines

Requirements:

• Bachelor's degree in Computer Science, Information Systems, Health Informatics, Data Analytics, Health Information Management, or a related field, or equivalent practical experience
• 5+ years of experience working with healthcare data, healthcare interoperability, clinical data integration, health informatics, or a closely related area
• Hands-on experience analyzing and working with CCD/C-CDA clinical documents, including XML structure, sections, entries, templates, identifiers, and clinical coding
• Hands-on experience with FHIR, including common clinical resources, Bundles, references, profiles, REST APIs, and JSON/XML representations
• Strong SQL skills and practical Python experience for parsing, transformation, automation, validation, and analysis of large healthcare datasets
• Working knowledge of healthcare interoperability concepts and standards, including HL7, C-CDA/CCD, FHIR, APIs, and common healthcare code systems and terminologies
• Experience profiling unfamiliar healthcare data sources and translating source-specific structures into standardized or normalized data models
• Experience troubleshooting data quality, mapping, ingestion, and integration issues across multiple vendors or source systems
• Strong analytical, problem-solving, communication, and technical documentation skills, with the ability to explain complex data issues to both technical and business stakeholders
• Experience with HEDIS, NCQA quality reporting, supplemental data, digital quality measurement, or Medical Record Review (MRR)
• Experience evaluating clinical data for quality-measure use cases and determining which document sections, coded facts, and source types provide meaningful reporting value
• Experience with clinical terminology and value-set concepts, including LOINC, SNOMED CT, ICD-10-CM, CPT/HCPCS, and RxNorm
• Experience with AWS or other cloud-based data and analytics environments, including large-scale file processing and automated data pipelines
• Experience working with health information exchanges, EHR vendors, clinical data aggregators, or payer-provider interoperability initiatives